обновлено 2 месяца назад
MLOps Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
MLOps Engineer (AI): Building and maintaining scalable ML systems, data pipelines, and model workflows for AI-powered demand prediction with an accent on data consistency, production readiness, and reliable model training and inference. Focus on orchestrating pipelines, processing structured and unstructured data, and operating distributed containerized systems with Docker and Kubernetes.
Location: Tel Aviv, Israel
Company
builds responsible AI systems that transform market complexity into profit growth through transparent demand prediction and pricing intelligence.
What you will do
- Build and maintain models and data pipelines supporting data science workflows.
- Process structured and unstructured data from multiple sources for model training and inference.
- Improve the accuracy, consistency, and efficiency of data used by machine learning systems.
- Develop scalable, production-ready ML systems and infrastructure.
- Collaborate with the Large Market Modeling team to bring demand models into production.
Requirements
- BSc or Master's degree in Computer Science, Mathematics, Engineering, or a related field.
- At least 5 years of commercial Python experience.
- At least 3 years of hands-on commercial MLOps experience.
- Experience with pipeline orchestrators such as Dagster or Airflow and with distributed computing systems.
- Experience with Docker and Kubernetes or other scalable containerized solutions.
- Fluent English, written and spoken.
Nice to have
- Aviation industry experience.
- Strong understanding of data structures and algorithms.
- Proactive approach and ability to suggest improved solutions.
Culture & Benefits
- Work in a high-growth startup environment.
- Contribute to responsible and transparent AI systems.
- Collaborate with a team focused on impactful pricing, forecasting, and optimization technology.
- Supportive team-player culture with a readiness to help others.
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